Most previous works on text classification, represented importance of terms by term occurrence frequency (tf) and inverse document frequency (idf). This paper presents the ways to apply class frequency in centroid-based text categorization. Three approaches are taken into account. The first one is to explore the effectiveness of inverse class frequency on the popular term weighting, i.e., TFIDF...

Word Sense Disambiguation (WSD) is the task of computational assignment of correct sense of a polysemous word in a given context. This paper compares three WSD algorithms for Hindi WSD based on corpus statistics. The first algorithm, called corpus-based Lesk, uses sense definitions and a sense tagged training corpus to learn weights of Content Words (CWs). These weights are used in the disambig...

SYNONYM Within-element term frequency, Inverse element frequency DEFINITION Classical ranking algorithms in information retrieval make use of term statistics, the most common (and basic) ones being within-document term frequency, tf, and document frequency, df. tf is the number of occurrences of a term in a document and is used to reflect how well a term captures the topic of a document, wherea...

We propose a method to mine novel, document-specific associations between terms in a collection of unstructured documents. We believe that documents are often best described by the relationships they establish. This is also evidenced by the popularity of conceptual maps, mind maps, and other similar methodologies to organize and summarize information. Our goal is to discover term relationships ...

The use of social media is very influential for the community. Users can easily post various activities in form text, photos, and videos media. Information on contains fake news hoaxes that will have an impact society. One most used Twitter. This study aims to detect found Tweets using Convolutional Neural Network (CNN) method by comparing weighting features Term Frequency Inverse Document (TF-...

Laporan kasus tindak kekerasan dan pelecehan seksual pada perempuan anak yang diterima oleh Dinas Pemberdayaan Perempuan Perlindungan Anak (DP3A) dalam melakukan rekap pengelompokan laporan masih dilakukan secara manual. Penelitian untuk membuat model klasifikasi berdasarkan kronologi kejadian kedalam beberapa kategori jenis dengan memanfaatkan Text Mining. Tahapan sesuai tahapan metode Knowled...

For bounded datasets such as the TRECWeb Track (WT10g) the computation of term frequency (TF) and inverse document frequency (IDF) is not difficult. However, when the corpus is the entire web, direct IDF calculation is impossible and values must instead be estimated. Most available datasets provide values for term count (TC) meaning the number of times a certain term occurs in the entire corpus...

Text clustering and classification are two main tasks of text mining. Feature selection plays the key role in the quality of the clustering and classification results. Although word-based features such as term frequency-inverse document frequency (TF-IDF) vectors have been widely used in different applications, their shortcoming in capturing semantic concepts of text motivated researches to use...